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How to build a successful AI strategy

IBM Big Data Hub

An AI strategy allows organizations to purposefully harness AI capabilities and align AI initiatives with overall business objectives. It will also determine the talent the organization needs to develop, attract or retain with relevant skills in data science, machine learning (ML) and AI development.

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Cloud Analytics Powered by FinOps

Cloudera

Agility, innovation, and time-to-value are the key differentiators cloud service providers (CSP) claim to help organizations speed up digital transformation projects and business objectives. However, the reality is that the “move to cloud” is a turbulent flight for many of them. Why FinOps?

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How Encored Technologies built serverless event-driven data pipelines with AWS

AWS Big Data

Encored develops machine learning (ML) applications predicting and optimizing various energy-related processes, and their key initiative is to predict the amount of power generated at renewable energy power plants. For instructions on creating an ECR repository, refer to Creating a private repository. northeast-2.amazonaws.com

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Automating Model Risk Compliance: Model Validation

DataRobot Blog

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. If we have already built out a model for a business application, how do we ensure that it is working to our expectations? Conceptual Soundness of the Model.

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4 Recommendations for Maximizing ROI in Artificial Intelligence Solutions

CDW Research Hub

As AI use cases start meeting their initial business objectives, initial infrastructure decisions can either accelerate the deployment of subsequent use cases or stall them. Businesses should be ready to adapt to these outcomes while being flexible regarding infrastructure. Understanding the workflow requirements is critical.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. There’s A Wealth Of Choice. They can help a company forecast demand, or anticipate fraud.

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Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue

AWS Big Data

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. You will see the message “Successfully connected to the data store with connection blog-redshift-connection.” Choose Confirm.

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